Category Archives: simple explanation

Summary of the NIR Chemometric survey polls (as of end of Sept. 2013)

The interesting finding is that most of the answers fit the following pattern. The most companies that use NIR have one NIR Instrument and only one employee that is able to develop NIR calibrations. For that the most common off-the-shelf chemometrics program is used and spent 2 hours or over a month and therefore gets no calibration training about the complex topics like Chemometrics and NIR Spectroscopy or only once (introduction). The calibration maintenance ranges from never to 3 times a year. Interestingly, there was no one who uses portable NIR instruments. We continue our surveys, for the discovery of new trends. Conclusion Seeing this picture, we think that there is huge potential to improve the calibrations. Advanced knowledge can help individuals to build the calibrations with best practices and improve their models accuracy and reliability. Once the decision and investment in NIR technology is done, you should get the best out of your data, because this extra NIR performance can be given by calibration optimization. We offer this as an easy to use and independent service.

The NIR analysis is a very fast non-destructive analysis method that can replace or backup slower methods like wet chemical analysis, chemistry laboratory, sensory panels or rheology (viscosity).
Or a NIR calibration can open the door to new possibilities of analytics, quality assurance and process control, by developing calibration models for parameters that seems to be impossible, because they are based on human knowledge, empirical values or sensory like taste value.
If you have an NIR instrument, you can measure your samples systematically and thus develop your own calibration models.

There are a lot of terms that means the same,
pre-calibration or NIR starter calibration or pre-built calibration or pre-installed calibration orcalibration package or pre-developed calibrations or pre-calibrated NIR or global calibrations or nir global calibration package or factory calibrations or universal near-infrared (NIR) calibrations orlocal calibrations or ready-to-use NIR calibrations or off-the-shelf calibrations or factory-calibrated or pre calculated model or start-up calibrations or calibration equations orprefabricated nir calibrations or calibration library or mathematical model.
That are Calibration models that are prepared and developed by a calibration specialist. They have collected a lot of samples over years and measured them with NIR and analyced it with reference methods.
The NIR spectra are then calibrated against the reference values. This is called a NIR calibration or calibration model or sometimes calibration curve or calibration equation.
Normally a precalibration is delivered as a file that is compatible to the used NIR analysis software. Such a calibration file does not contain the spectra nor the reference values.

So how can that work?

The only thing that is in the file is a description what it is for (e.g. protein in feed) and the chemometric model that is represented and stored as list of vectors and matrices.
You can’t visualize them, it’s a black-box file. You have no insight of how the calibration is done, how are the settings, how is the prediction performance. You can not extend the calibration with your data to adjust it to your purpose or specialty.
Most often the pre calibration files are protected, so you can use it only with a paid license to your software or even to your instrument serials number.
These are some (not well known) limitations you will discover if you got one.
But such starter calibrations are very useful to have a fast and easy start with a new NIR spectrometer. That’s the main reason why pre-calibrations are available. The second reason is that a collection of spectra can be reused to build such pre calibrations.

Predicting the future?

Are very old spectra useful to predict the future? To adjust a calibration model with newly collected data, the calibrations grows and contains more and more redundancy.
That means there are very similar spectra with the same concentration range.
So which spectra can be removed to make the calibration better? You maybe never ask this because often you hear, that the more spectra you put into a model the better it will be.
Why to remove some spectra?

reduce not needed redundancy

makes the calibration smaller and less complex

makes the calibration better fit to the current situation of now and the near future

remove long past seasonal data if you have natural products because nature is changing

and of course bad outliers should be removed

Custom NIR calibrations

Build your own calibrations that perfectly fit to your specific sample matrix of your products and your preferred raw materials from your local suppliers.
Nature grows differently depending on the geographical region, by seasons and year by year. As you know that NIR-Spectroscopy is not an absolute method, then you have to think about to calibrate these current changing effects into your models.
If you own the spectra and the reference values then your are able to build your own calibration models and re-calibrate them when needed. So you have the full control on Calibration updates (also known as moving models).

Conclusion

A NIR-instrument can only measure NIR spectra. So the usefulness of NIR comes in with calibrations. That is very important to know when buying such an instrument. For a fast start you can use pre-built calibrations. Good reliably calibrations are offered from third party to quite high prices that level is similar to a cheaper NIR-Instrument!
To continue successfully it is highly recommended to develop your own customized calibration (multivariate calibration model) with your own data from your own products, especially with the use of natural resources. Therefore you need knowledge about chemometrics and multivariate analysis (MVA), spectroscopy and the software used to get the calibration optimized.
It is worthwhile to create your own calibrations, because you can calibrate product characteristics that are not covered by the proposed pre-calibrations.

JCAMP-DX is a Electronic Data Standards for long-term storage and transfer of chemometric information. The standard is development by the International Union of Pure and Applied Chemistry (IUPAC).

JCAMP-DX is an abreviation for the Joint Committee on Atomic and Molecular Physical data – Data eXchange.

It is an human readable file format that is used to store near infrared spectrometry data (and others like Raman, UV, NMR, mass, x-ray, chromatograms, thermograms) and relatedchemical and physical information and is used since the late 80s.

Almost all NIR-software packages can export the spectra including the reference values as JCAMP-DX. A single file can contain multiple spectra and reference values.
A JCAMP file name looks like “sample.dx“, “sample.jdx” or “sample.jcm“.

All data are stored as labeled fields of variable length using printable ASCII characters.
Such files can be loaded in an text editor to check the content:

In the most cases a simple Halogen lamp emits light including the near infrared (NIR)spectrum (harmless radiation) to the sample/probe and the reflected light is measured. The light loses some energy on-and-in the sample depending on its physical and chemical (molecular) structure. The missing part of the light is treated as a fingerprint of the sample that is mathematically analyzed with prefabricated NIR calibration models (built with chemometric methods), based on trained known samples. That makes it possible to simultaneous analyze multiple physical- and chemical-properties (constituent, ingredient, analyte) within a few seconds and is non-destructive to samples.

To explain our service in an other way, I use an analogy between a book and a calibration. Building good calibrations is like writing a good book (a bestseller). You can write in a foreign language (chemometrics) with a high sophisticated word-processor (the chemometric software) that has a grammar checker (an outlier detection).
Due to the complexity of the language (chemometrics) and the difficulty of the chosen book topic (the data) and the incomplete automatic grammar checker, you can never be sure if the grammar is correct and may not lead to misunderstanding (bad prediction performance).
So the best way is to let a native language speaker check and correct the text.
In that way (the analogy), you can see us even as a ghostwriter (a ghost calibration developer, a ghostcalibrator) that helps you, writing the book (with long year experience, consolidated knowledge, time saving, a lot of benefit).
The analogy fits very well, because you can define the topic of the book (with your data). Finally you own the calibration and you have the full insight in how it is done. You have it under full control.